News Release

Microrobotic swarms for cancer therapy

Peer-Reviewed Publication

Research

Fig. 1. Schematic illustration of 5 aspects of microrobotic swarms in cancer therapy.

image: 

Fig. 1. Schematic illustration of 5 aspects of microrobotic swarms in cancer therapy.

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Credit: Copyright © 2025 Leiming Xie et al.

Background

Cancer remains one of the most challenging diseases to treat, as conventional therapies like chemotherapy and radiotherapy are often hindered by poor specificity, systemic toxicity, and damage to healthy tissues. In contrast, microrobotic swarms have emerged as a transformative approach, providing enhanced targeting precision, multimodal therapy, and minimally invasive capabilities. Unlike conventional methods that rely on passive diffusion or systemic circulation, microrobotic swarms actively navigate complex biological environments to deliver therapeutic agents directly to tumor sites, thereby reducing off-target effects and enabling real-time monitoring. These swarms can perform multiple functions simultaneously, such as drug delivery, imaging, and hyperthermia, while adapting to dynamic environments for precise cancer treatment.

Prof. Jiangfan Yu's team at the School of Science and Engineering, The Chinese University of Hong Kong (Shenzhen), has summarized the applications of microrobots in cancer therapy from the perspective of swarms (Fig. 1). This review systematically discusses the design of microrobots for cancer therapy, focusing on three main strategies: tumor cell elimination, tumor infiltration, and tumor immunomodulation. Thereafter, the delivery and imaging strategies of swarms in vivo are introduced. Finally, the article summarizes current applications of microrobotic swarms across tumors in various organs and discusses the challenges and future directions to enhance cancer treatment efficiency.​

​​Design of Agents for Cancer Therapy

Addressing the characteristics of cancer, including uncontrolled proliferation, impenetrable microenvironments, and immunosuppression, this review thoroughly examines microrobotic strategies from three aspects: tumor cell eradication, improved tumor penetration, and reversal of immune suppression. While conventional chemotherapy targets malignant cells, its systemic toxicity and poor specificity cause significant collateral damage to healthy tissues. The review systematically analyzes the design of microrobots developed for targeted chemotherapeutic delivery and multimodal therapy (combining gene therapy, oncolytic viruses, and phototherapy) (Fig. 2). Additionally, microenvironment-responsive microrobots are discussed, including oxygen-generating microrobots that catalytically decompose hydrogen peroxide to reduce hypoxia and magnetotactic bacteria that autonomously swim toward oxygen-deprived tumor regions. To combat tumor immunosuppression, the article describes microrobotic design strategies that promote immune infiltration and enhance CAR-T cell efficacy against solid tumors (Fig. 3).

Delivery and Imaging of Microrobotic Swarms in Cancer Therapy

Conventional nanomedicines mainly depend on passive diffusion and the Enhanced Permeability and Retention (EPR) effect for tumor accumulation, but mounting evidence shows that only about 0.7% of administered nanodrugs reach solid tumors, greatly limiting their clinical effectiveness. In contrast, microrobotic swarms combine the benefits of traditional nanocarriers, such as drug protection, selectivity, and biocompatibility, with active propulsion capabilities, which have the potential to significantly improve both long-range and short-distance targeted drug delivery. This review describes three advanced long-range delivery strategies (Fig. 4): real-time guided swarm navigation, potential well-based delivery, and autonomously motile swarm systems. Additionally, the article discusses methods for real-time in vivo swarm tracking using fluorescence, ultrasound, MRI, and photoacoustic imaging technologies. Importantly, when these swarms reach tumor sites, they can serve as contrast agents for tumor imaging and biosensing simultaneously, ultimately enabling precise drug delivery with spatiotemporal control (Fig. 5).

Microrobotic Swarms Enabled Cancer Therapy

Cancers occurring in different organs possess distinct biological characteristics, and the corresponding treatment approaches vary accordingly. This review summarizes the typical work of microrobotic swarms for cancer therapy of different organs. By addressing unique pathophysiological barriers such as the blood-brain barrier in brain cancer, branched airway architecture in lung cancer, and immunosuppressive microenvironments in liver cancer, the review proposes tailored microrobotic approaches specifically engineered for each organ context (Fig. 6).​

Future Prospects

Microrobotic swarms hold tremendous potential for revolutionizing cancer treatment by enabling precise, targeted drug delivery and real-time therapeutic monitoring. However, to realize their full clinical potential, continued research is needed to address the existing challenges. Significant biocompatibility concerns persist, including material toxicity (e.g., the release of harmful ions from metallic nanoparticles), immune clearance (requiring strategies such as PEGylation or CD47 labeling to prolong circulation time), and off-target risks (necessitating magnetic navigation coupled with tumor-targeting ligands for enhanced precision). Furthermore, dense extracellular matrices and immunosuppressive microenvironments substantially impede swarm penetration into tumors. Overcoming these barriers demands the design of multifunctional hybrid systems, such as magnetically engineered bacteria, that integrate both autonomous motility and externally driven mechanisms (e.g., magnetic, acoustic fields). Finally, while current research remains largely confined to small-animal models, clinical translation urgently requires developing human-scale swarm actuation systems and intelligent control platforms incorporating advanced algorithms (reinforcement learning, swarm intelligence) to dramatically improve operational reliability and navigation accuracy within complex physiological environments.​

Sources: https://spj.science.org/doi/10.34133/research.0686


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